15 resultados para predictive regression model

em Helda - Digital Repository of University of Helsinki


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Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.

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The focus of this study is on statistical analysis of categorical responses, where the response values are dependent of each other. The most typical example of this kind of dependence is when repeated responses have been obtained from the same study unit. For example, in Paper I, the response of interest is the pneumococcal nasopharengyal carriage (yes/no) on 329 children. For each child, the carriage is measured nine times during the first 18 months of life, and thus repeated respones on each child cannot be assumed independent of each other. In the case of the above example, the interest typically lies in the carriage prevalence, and whether different risk factors affect the prevalence. Regression analysis is the established method for studying the effects of risk factors. In order to make correct inferences from the regression model, the associations between repeated responses need to be taken into account. The analysis of repeated categorical responses typically focus on regression modelling. However, further insights can also be gained by investigating the structure of the association. The central theme in this study is on the development of joint regression and association models. The analysis of repeated, or otherwise clustered, categorical responses is computationally difficult. Likelihood-based inference is often feasible only when the number of repeated responses for each study unit is small. In Paper IV, an algorithm is presented, which substantially facilitates maximum likelihood fitting, especially when the number of repeated responses increase. In addition, a notable result arising from this work is the freely available software for likelihood-based estimation of clustered categorical responses.

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The factors affecting the non-industrial, private forest landowners' (hereafter referred to using the acronym NIPF) strategic decisions in management planning are studied. A genetic algorithm is used to induce a set of rules predicting potential cut of the landowners' choices of preferred timber management strategies. The rules are based on variables describing the characteristics of the landowners and their forest holdings. The predictive ability of a genetic algorithm is compared to linear regression analysis using identical data sets. The data are cross-validated seven times applying both genetic algorithm and regression analyses in order to examine the data-sensitivity and robustness of the generated models. The optimal rule set derived from genetic algorithm analyses included the following variables: mean initial volume, landowner's positive price expectations for the next eight years, landowner being classified as farmer, and preference for the recreational use of forest property. When tested with previously unseen test data, the optimal rule set resulted in a relative root mean square error of 0.40. In the regression analyses, the optimal regression equation consisted of the following variables: mean initial volume, proportion of forestry income, intention to cut extensively in future, and positive price expectations for the next two years. The R2 of the optimal regression equation was 0.34 and the relative root mean square error obtained from the test data was 0.38. In both models, mean initial volume and positive stumpage price expectations were entered as significant predictors of potential cut of preferred timber management strategy. When tested with the complete data set of 201 observations, both the optimal rule set and the optimal regression model achieved the same level of accuracy.

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Objectives of this study were to determine secular trends of diabetes prevalence in China and develop simple risk assessment algorithms for screening individuals with high-risk for diabetes or with undiagnosed diabetes in Chinese and Indian adults. Two consecutive population based surveys in Chinese and a prospective study in Mauritian Indians were involved in this study. The Chinese surveys were conducted in randomly selected populations aged 20-74 years in 2001-2002 (n=14 592) and 35-74 years in 2006 (n=4416). A two-step screening strategy using fasting capillary plasma glucose (FCG) as first-line screening test followed by standard 2-hour 75g oral glucose tolerance tests (OGTTs) was applied to 12 436 individuals in 2001, while OGTTs were administrated to all participants together with FCG in 2006 and to 2156 subjects in 2002. In Mauritius, two consecutive population based surveys were conducted in Mauritian Indians aged 20-65 years in 1987 and 1992; 3094 Indians (1141 men), who were not diagnosed as diabetes at baseline, were reexamined with OGTTs in 1992 and/or 1998. Diabetes and pre-diabetes was defined following 2006 World Health Organization/ International Diabetes Federation Criteria. Age-standardized, as well as age- and sex-specific, prevalence of diabetes and pre-diabetes in adult Chinese was significantly increased from 12.2% and 15.4% in 2001 to 16.0% and 21.2% in 2006, respectively. A simple Chinese diabetes risk score was developed based on the data of Chinese survey 2001-2002 and validated in the population of survey 2006. The risk scores based on β coefficients derived from the final Logistic regression model ranged from 3 – 32. When the score was applied to the population of survey 2006, the area under operating characteristic curve (AUC) of the score for screening undiagnosed diabetes was 0.67 (95% CI, 0.65-0.70), which was lower than the AUC of FCG (0.76 [0.74-0.79]), but similar to that of HbA1c (0.68 [0.65-0.71]). At a cut-off point of 14, the sensitivity and specificity of the risk score in screening undiagnosed diabetes was 0.84 (0.81-0.88) and 0.40 (0.38-0.41). In Mauritian Indian, body mass index (BMI), waist girth, family history of diabetes (FH), and glucose was confirmed to be independent risk predictors for developing diabetes. Predicted probabilities for developing diabetes derived from a simple Cox regression model fitted with sex, FH, BMI and waist girth ranged from 0.05 to 0.64 in men and 0.03 to 0.49 in women. To predict the onset of diabetes, the AUC of the predicted probabilities was 0.62 (95% CI, 0.56-0.68) in men and 0.64(0.59-0.69) in women. At a cut-off point of 0.12, the sensitivity and specificity was 0.72(0.71-0.74) and 0.47(0.45-0.49) in men; and 0.77(0.75-0.78) and 0.50(0.48-0.52) in women, respectively. In conclusion, there was a rapid increase in prevalence of diabetes in Chinese adults from 2001 to 2006. The simple risk assessment algorithms based on age, obesity and family history of diabetes showed a moderate discrimination of diabetes from non-diabetes, which may be used as first line screening tool for diabetes and pre-diabetes, and for health promotion purpose in Chinese and Indians.

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This research discusses decoupling CAP (Common Agricultural Policy) support and impacts which may occur on grain cultivation area and supply of beef and pork in Finland. The study presents the definitions and studies on decoupled agricultural subsidies, the development of supply of grain, beef and pork in Finland and changes in leading factors affecting supply between 1970 and 2005. Decoupling agricultural subsidies means that the linkage between subsidies and production levels is disconnected; subsidies do not affect the amount produced. The hypothesis is that decoupling will decrease the amounts produced in agriculture substantially. In the supply research, the econometric models which represent supply of agricultural products are estimated based on the data of prices and amounts produced. With estimated supply models, the impacts of changes in prices and public policies, can be forecasted according to supply of agricultural products. In this study, three regression models describing combined cultivation areas of rye, wheat, oats and barley, and the supply of beef and pork are estimated. Grain cultivation area and supply of beef are estimated based on data from 1970 to 2005 and supply of pork on data from 1995 to 2005. The dependencies in the model are postulated to be linear. The explanatory variables in the grain model were average return per hectare, agricultural subsidies, grain cultivation area in the previous year and the cost of fertilization. The explanatory variables in the beef model were the total return from markets and subsidies and the amount of beef production in the previous year. In the pork model the explanatory variables were the total return, the price of piglet, investment subsidies, trend of increasing productivity and the dummy variable of the last quarter of the year. The R-squared of model of grain cultivation area was 0,81, the model of beef supply 0,77 and the model of pork supply 0,82. Development of grain cultivation area and supply of beef and pork was estimated for 2006 - 2013 with this regression model. In the basic scenario, development of explanatory variables in 2006 - 2013 was postulated to be the same as they used to be in average in 1995 - 2005. After the basic scenario the impacts of decoupling CAP subsidies and domestic subsidies on cultivation area and supply were simulated. According to the results of the decoupling CAP subsidies scenario, grain cultivation area decreases from 1,12 million hectares in 2005 to 1,0 million hectares in 2013 and supply of beef from 88,8 million kilos in 2005 to 67,7 million kilos in 2013. Decoupling domestic and investment subsidies will decrease the supply of pork from 194 million kilos in 2005 to 187 million kilos in 2006. By 2013 the supply of pork grows into 203 million kilos.

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The tackling of coastal eutrophication requires water protection measures based on status assessments of water quality. The main purpose of this thesis was to evaluate whether it is possible both scientifically and within the terms of the European Union Water Framework Directive (WFD) to assess the status of coastal marine waters reliably by using phytoplankton biomass (ww) and chlorophyll a (Chl) as indicators of eutrophication in Finnish coastal waters. Empirical approaches were used to study whether the criteria, established for determining an indicator, are fulfilled. The first criterion (i) was that an indicator should respond to anthropogenic stresses in a predictable manner and has low variability in its response. Summertime Chl could be predicted accurately by nutrient concentrations, but not from the external annual loads alone, because of the rapid affect of primary production and sedimentation close to the loading sources in summer. The most accurate predictions were achieved in the Archipelago Sea, where total phosphorus (TP) and total nitrogen (TN) alone accounted for 87% and 78% of the variation in Chl, respectively. In river estuaries, the TP mass-balance regression model predicted Chl most accurately when nutrients originated from point-sources, whereas land-use regression models were most accurate in cases when nutrients originated mainly from diffuse sources. The inclusion of morphometry (e.g. mean depth) into nutrient models improved accuracy of the predictions. The second criterion (ii) was associated with the WFD. It requires that an indicator should have type-specific reference conditions, which are defined as "conditions where the values of the biological quality elements are at high ecological status". In establishing reference conditions, the empirical approach could only be used in the outer coastal water types, where historical observations of Secchi depth of the early 1900s are available. The most accurate prediction was achieved in the Quark. In the inner coastal water types, reference Chl, estimated from present monitoring data, are imprecise - not only because of the less accurate estimation method but also because the intrinsic characteristics, described for instance by morphometry, vary considerably inside these extensive inner coastal types. As for phytoplankton biomass, the reference values were less accurate than in the case of Chl, because it was possible to estimate reference conditions for biomass only by using the reconstructed Chl values, not the historical Secchi observations. An paleoecological approach was also applied to estimate annual average reference conditions for Chl. In Laajalahti, an urban embayment off Helsinki, strongly loaded by municipal waste waters in the 1960s and 1970s, reference conditions prevailed in the mid- and late 1800s. The recovery of the bay from pollution has been delayed as a consequence of benthic release of nutrients. Laajalahti will probably not achieve the good quality objectives of the WFD on time.    The third criterion (iii) was associated with coastal management including the resources it has available. Analyses of Chl are cheap and fast to carry out compared to the analyses of phytoplankton biomass and species composition; the fact which has an effect on number of samples to be taken and thereby on the reliability of assessments. However, analyses on phytoplankton biomass and species composition provide more metrics for ecological classification, the metrics which reveal various aspects of eutrophication contrary to what Chl alone does.

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Tavoitteena oli tutkia 40-vuotiaiden miesten terveyskäyttäytymistä, terveysuskomuksia ja miesten saamaa terveysneuvontaa Helsingissä. 273 miestä vastasi kyselyyn ja osallistui terveystutkimuksiin. Terveydentilan perusteella miehet arvioitiin matalan (n=145) ja korkean (n=128) riskin ryhmiin. Khin neliö-testillä tutkittiin elämäntapa- ja riskitekijöitä koetun terveyden (hyvä, keskinkertainen/huono) luokissa ja verrattiin matalan ja korkean riskin ryhmiä em. tekijöiden osalta. Askeltavalla logistisella regressiomallilla analysoitiin tulosmuuttujia taustatekijöiden, terveyskäyttäytymisen, terveysuskomusten ja kliinisten riskitekijöiden avulla sekä arvioitiin oireiden ja vaivojen suhdetta koettuun terveydentilaan. Korkeassa riskissä olevien terveyttä seurattiin vuosina 2001–2004 analysoimalla mini-intervention vaikutusta terveysriskeihin ja elintapoihin varianssianalyysin avulla (ANOVA) (n=46). Matalasta vastausprosentista johtuen (39.6%), ei-vastanneiden aineistoa kerättiin käyttämällä syvähaastattelua (n=28) sekä puhelinkyselyä (n=40). Lopullinen aineisto koostui 341 miehestä. Tulokset osoittivat, että miehillä oli sydän- ja verisuonitautiriskejä. Kaksi kolmesta osallistuneista oli ylipainoisia tai lihavia, yli kolmanneksella vyötärönympärys oli ≥100 cm, ja yli 40%:llä oli diastolinen verenpaine ≥90 mmHg. Yli puolet tupakoi päivittäin ja 40% käytti alkoholia runsaasti. Ristiriitaisuutta ilmensi se, että huolimatta riskitekijöistä noin puolet miehistä koki terveydentilansa hyväksi. Sairauden tai vamman puute, hyvä suun terveydentila ja normaali vyötärönympärys olivat yhteydessä hyväksi koettuun terveydentilaan. Suora yhteys voitiin havaita omaisten tarjoaman neuvonnan ja vähäisen alkoholin käytön välillä. Masennus ja unettomuus olivat voimakkaasti yhteydessä loppuun palamiseen. Miehillä oli erilaisia fyysisiä ja psyykkisiä oireita, jotka korreloivat voimakkaasti masennuksen kanssa. Pieni määrä miehistä koki saaneensa terveysneuvontaa hoitohenkilökunnalta verrattuna perheenjäseniltä saatuun ohjaukseen. Korkeariskisten miesten (n=46) arvot parantuivat merkitsevästi lyhyellä aikavälillä. Kolesteroliarvoja lukuunottamatta ne palautuivat kolmen vuoden kuluttua alkumittausarvoja kohti. Laadullinen tutkimus osoitti, että “ei-vastanneet“ eivät osallistuneet projektiin, sillä he olivat oireettomia tai kiireisiä. Heillä todettiin samoja terveysriskejä kuin projektiin osallistuneilla. Syvähaastattelussa miehet toivat esille kokemuksiaan huolista, vihan tunteista, peloista ja yksinäisyydestä. Hoidonantajien on tärkeää ymmärtää ristiriidat miesten subjektiivisen ja objektiivisen terveydentilan välillä, mikä auttaa havaitsemaan esteitä terveyskäyttäytymiselle. Yhä enemmän tarvitaan yhteistyötä yksityisen ja julkisen terveydenhuollon välillä varmistamaan terveystottumusten jatkuminen miesten keskuudessa.

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The incidence of gastric cancer in the last decades has declined rapidly in the industrialised countries. Worldwide, however, gastric cancer is still the second most common cause of cancer death. Although surgery is currently the most effective treatment, the rapid progress in adjuvant chemotherapy and radiation therapy requires a re-evaluation of prognosis assessment. The TNM staging system of the UICC is ubiquitously used; it groups patients by decreasing survival times from stage I to stage IV based on the spread of disease, i.e. depth of tumour penetration (T), extent of spread to lymph nodes (N), and the presence or absence of distant (M) metastases. This is by far the most consistent prognostic classification system today. However, even within the stage groups there are patients that follow a varying course of disease. Our knowledge of the molecular differences between tumours of the same stage and morphology has been accumulating over the years and methods for a more accurate assessment of the phenotype of neoplasias are of value when evaluating the prognosis of individual patients with gastric cancer. In this study, the immunohistochemical expression of tumour markers involved in different phases in tumourigenesis was examined. The aim was to find new markers which could provide prognostic information in addition to what is provided by the TNM variables. A total of 337 specimens from the primary tumour of patients who underwent surgery for gastric cancer were collected and the immunohistochemical expression of seven different biomarkers was analysed. DNA ploidy and S-phase fraction (SPF) was assessed by flow cytometry. Finally, all biomarkers and clinicopathological prognostic factors were combined and evaluated by a multivariate Cox regression model to elucidate which specific factors provide independent prognostic information. By univariate survival analysis the following variables were significant prognostic factors: epithelial and stromal syndecan-1 expression, stromal tenascin-C expression, expression of tumour-associated trypsin inhibitor (TATI) in cancer cells, nuclear p53 expression, nuclear p21 expression, DNA ploidy, and SPF. By multivariate survival analysis adjusted for all available clinicopathological and biomolecular variables, p53 expression, p21 expression, and DNA ploidy emerged as independent prognostic biomarkers, together with penetration depth of the tumour, presence of nodal metastases, surgical cure of the cancer, and age of the patient at the time of diagnosis.

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Congenital long QT syndrome (LQTS) with an estimated prevalence of 1:2000-1:10 000 manifests with prolonged QT interval on electrocardiogram and risk for ventricular arrhythmias and sudden death. Several ion channel genes and hundreds of mutations in these genes have been identified to underlie the disorder. In Finland, four LQTS founder mutations of potassium channel genes account for up to 40-70% of genetic spectrum of LQTS. Acquired LQTS has similar clinical manifestations, but often arises from usage of QT-prolonging medication or electrolyte disturbances. A prolonged QT interval is associated with increased morbidity and mortality not only in clinical LQTS but also in patients with ischemic heart disease and in the general population. The principal aim of this study was to estimate the actual prevalence of LQTS founder mutations in Finland and to calculate their effect on QT interval in the Finnish background population. Using a large population-based sample of over 6000 Finnish individuals from the Health 2000 Survey, we identified LQTS founder mutations KCNQ1 G589D (n=8), KCNQ1 IVS7-2A>G (n=1), KCNH2 L552S (n=2), and KCNH2 R176W (n=16) in 27 study participants. This resulted in a weighted prevalence estimate of 0.4% for LQTS in Finland. Using a linear regression model, the founder mutations resulted in a 22- to 50-ms prolongation of the age-, sex-, and heart rate-adjusted QT interval. Collectively, these data suggest that one of 250 individuals in Finland may be genetically predisposed to ventricular arrhythmias arising from the four LQTS founder mutations. A KCNE1 D85N minor allele with a frequency of 1.4% was associated with a 10-ms prolongation in adjusted QT interval and could thus identify individuals at increased risk of ventricular arrhythmias at the population level. In addition, the previously reported associations of KCNH2 K897T, KCNH2 rs3807375, and NOS1AP rs2880058 with QT interval duration were confirmed in the present study. In a separate study, LQTS founder mutations were identified in a subgroup of acquired LQTS, providing further evidence that congenital LQTS gene mutations may underlie acquired LQTS. Catecholaminergic polymorphic ventricular tachycardia (CPVT) is characterized by exercise-induced ventricular arrhythmias in a structurally normal heart and results from defects in the cardiac Ca2+ signaling proteins, mainly ryanodine receptor type 2 (RyR2). In a patient population of typical CPVT, RyR2 mutations were identifiable in 25% (4/16) of patients, implying that noncoding variants or other genes are involved in CPVT pathogenesis. A 1.1 kb RyR2 exon 3 deletion was identified in two patients independently, suggesting that this region may provide a new target for RyR2-related molecular genetic studies. Two novel RyR2 mutations showing a gain-of-function defect in vitro were identified in three victims of sudden cardiac death. Extended pedigree analyses revealed some surviving mutation carriers with mild structural abnormalities of the heart and resting ventricular arrhythmias suggesting that not all RyR2 mutations lead to a typical CPVT phenotype, underscoring the relevance of tailored risk stratification of a RyR2 mutation carrier.

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Tämän tutkimuksen tavoitteena oli selvittää tilalla määritetyn hyvinvoinnin yhteyttä emakoiden tuotantotuloksiin. Hyvinvointia arvioitiin suomalaisen hyvinvointi-indeksin, A-indeksi, avulla. Tuotantotuloksina käytettiin kahta erilaista tuotosaineistoa, jotka molemmat pohjautuivat kansalliseen tuotosseuranta aineistoon. Hyvinvointimääritykset tehtiin 30 porsastuotantosikalassa maaliskuun 2007 aikana. A-indeksi koostuu kuudesta kategoriasta ’liikkumismahdollisuudet’, ’alustan ominaisuudet’, ’sosiaaliset kontaktit’, ’valo, ilma ja melu’, ’ruokinta ja veden saanti’ sekä ’eläinten terveys ja hoidon taso’. Jokaisessa kategoriassa on 3-10 pääosin ympäristöperäistä muuttujaa, jotka vaihtelevat osastoittain. Maksimipistemäärä osastolle on 100. Hyvinvointimittaukset tehtiin porsitus-, tiineytys- ja joutilasosastoilla. Erillisten tiineytysosastojen pienen lukumäärän takia (n=7) tilakohtaiset tiineytys- ja joutilasosastopisteet yhdistettiin ja keskiarvoja käytettiin analyyseissä. Yhteyksiä tuotokseen tutkittiin kahden eri aineiston avulla 1) Tilaraportti aineisto (n=29) muodostuu muokkaamattomista tila- ja tuotostuloksista tilavierailua edeltävän vuoden ajalta, 2) POTSIaineisto (n=30) muodostuu POTSI-ohjelmalla (MTT) muokatusta tuotantoaineistosta, joka sisältää managementtiryhmän (tila, vuosi, vuodenaika) vaikutuksen ensikoiden ja emakoiden pahnuekohtaiseen tuotokseen. Yhteyksiä analysointiin korrelaatio- ja regressioanalyysien avulla. Vaikka osallistuminen tutkimukseen oli vapaaehtoista, molempien tuotantoaineistojen perusteella tutkimustilat edustavat keskituottoista suomalaista sikatilaa. A-indeksin kokonaispisteet vaihtelivat välillä 37,5–64,0 porsitusosastolla ja 39,5–83,5 joutilasosastolla. Tilaraporttiaineistoa käytettäessä paremmat pisteet porsitusosaston ’eläinten terveys ja hoidon taso’ -kategoriasta lyhensivät eläinten lisääntymissykliä, lisäsivät syntyvien pahnueiden ja porsaiden määrää sekä alensivat kuolleena syntyneiden lukumäärää. Regressiomallin mukaan ’eläinten terveys ja hoidon taso’ -kategoria selitti syntyvien porsaiden lukumäärän, porsimisvälin pituuden sekä keskiporsimiskerran vaihtelua. Paremmat pisteet joutilasosaston ’liikkumismahdollisuudet’ kategoriasta alensivat syntyneiden pahnueiden sekä syntyneiden että vieroitettujen porsaiden lukumäärää. Regressiomallin mukaan ensikkopahnueiden osuus ja ”liikkumismahdollisuudet” kategorian pisteet selittivät vieroitettujen porsaiden lukumäärän vaihtelua. POTSI-aineiston yhteydessä kuolleena syntyneiden porsaiden lukumäärän aleneminen oli ensikoilla yhteydessä parempiin porsitusosaston ’sosiaalisiin kontakteihin’ ja emakoilla puolestaan joutilasosaston parempiin ’eläinten terveys ja hoidon taso’ pisteisiin. Kahden eri tuotantoaineiston avulla saadut tulokset erosivat toisistaan. Seuraavissa tutkimuksissa onkin suositeltavampaa käyttää Tilaraporttiaineistoja, joissa tuotokset ilmoitetaan vuosikohtaisina. Tämän tutkimuksen perusteella hyvinvoinnilla ja tuotoksella on yhteyksiä, joilla on myös merkittävää taloudellista vaikutusta. Erityisesti hyvä eläinten hoito ja eläinten terveys lisäävät tuotettujen porsaiden määrää ja lyhentävät lisääntymiskiertoa. Erityishuomiota tulee kiinnittää vapaana olevien joutilaiden emakoiden sosiaaliseen stressiin ja rehunsaannin varmistamiseen kaikille yksilöille.

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Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.

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Tutkielman tavoitteena on selvittää suomalaisen alkuperäiskarjan lihan potentiaalista kysyntää. Alkuperäiskarjan lihan erikoistuotemarkkinat voivat auttaa pitämään uhanalaiset, kotimaiset karjarodut tuotantokäytössä. Näin ollen erikoistuotemarkkinat voivat auttaa arvokkaiden suomalaisten eläingeenivarojen säilyttämisessä. Koska alkuperäiskarjan lihan tuotannon kannattavuus riippuu lihasta saatavasta lisähinnasta, tutkimuksen tavoitteena on myös tutkia, millainen kuluttajien maksuhalukkuus alkuperäiskarjan lihasta on verrattuna tavanomaiseen lihaan. Tutkimusaineisto kerättiin Maa- ja elintarviketalouden tutkimuskeskuksen ja Kuluttajatutkimuskeskuksen suunnittelemalla kyselytutkimuksella keväällä 2010. Tutkimuksessa käytettiin ehdollisen käyttäytymisen ja ehdollisen arvottamisen menetelmiä ja sen otoskoko on 1623. Kuluttajien ostohalukkuutta ja siihen vaikuttavia tekijöitä tutkittiin sekä binäärisen että ordinaalisen regression malleilla. Kuluttajien maksuhalukkuutta alkuperäiskarjan lihasta ja siihen vaikuttavia tekijöitä tutkittiin grouped data -mallin avulla. Malleissa käytettiin selittävinä muuttujina sosioekonomisten muuttujien lisäksi kuluttajien asenteita ja käyttäytymistä kuvaavia muuttujia. Tutkielman tulosten mukaan jopa 86 % vastaajista ostaisi alkuperäiskarjan lihaa, jos sitä olisi tarjolla kaupoissa. Ostohalukkuutta lisää muun muassa, jos vastaajalla on alle 18-vuotiaita lapsia ja vastaaja arvostaa lähellä tuotettua, paikallista ruokaa sekä ympäristöystävällisyyttä. Miehet ostaisivat alkuperäiskarjan lihaa todennäköisemmin kuin naiset. Suurin osa vastaajista ostaisi alkuperäiskarjan lihaa, jos se olisi samanhintaista kuin tavanomainen liha, mutta noin neljäsosa (23,5 %) vastaajista olisi valmis maksamaan alkuperäiskarjan lihasta korkeampaa hintaa kuin tavanomaisesta lihasta. Maksuhalukkuuteen vaikuttivat positiivisesti muun muassa kuuluminen ympäristöjärjestöön ja korkea tulotaso. Negatiivisesti vaikutti puolestaan esimerkiksi se, että vastaaja on nainen. Keskimääräinen maksuhalukkuus alkuperäiskarjan lihasta oli 6,25 % korkeampi kuin tavanomaisesta lihasta. Maksuhalukkuus alkuperäiskarjan lihasta oli selvästi yhteydessä siihen, kuinka usein vastaaja olisi halukas ostamaan sitä. Maksuhalukkuus oli korkein niillä vastaajilla, jotka haluaisivat ostaa lihaa säännöllisesti.

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During 1990 to 2009, Foreign Direct Investment (FDI henceforth) in Finland has fluctuated greatly. This paper focused on analyzing the overall development and basic characteristics of Foreign Direct Investment in Finland, covering the period from 1990 to present. By comparing FDI in Finland with FDI in other countries, the picture of Finland’s FDI position in the world market is clearer. A lot of statistical data, tables and figures are used to describe the trend of Foreign Direct Investment in Finland. All the data used in this study were obtained from Statistics Finland, UNCTAD, OECD, World Bank and International Labor Office, Investment map website and etc. It is also found that there is a big, long-lasting and increasing imbalance of the inward FDI and outward FDI in Finland, the performance of outward FDI is stronger than the inward FDI in Finland. Finland’s position of FDI in the world is rather modest. And based on existing theories, I tried to analyze the factors that might determine the size of the inflows of FDI in Finland. The econometric model of my thesis is based on time series data ranging from 1990 to 2007. A Log linear regression model is adopted to analyze the impact of each variable. The regression results showed that Labor Cost and Investment in Education have a negative influence on the FDI inflows into Finland. Too high labor cost is the main impediment of FDI in Finland, explaining the relative small size of FDI inflows into Finland. GDP and Economy openness have a significant positive impact on the inflows of FDI into Finland; other variables do not emerge as significant factor in affecting the size of FDI inflows in Finland as expected. Meanwhile, the impacts of the most recent financial and economic crisis on FDI in the world and in Finland are discussed as well. FDI inflows worldwide and in Finland have suffered from a big setback from the 2008 global crisis. The economic crisis has undoubtedly significant negative influence on the FDI flows in the world and in Finland. Nevertheless, apart from the negative impact, the crisis itself also brings in chances for policymakers to implement more efficient policies in order to create a pro-business and pro-investment climate for the recovery of FDI inflows. . The correspondent policies and measures aiming to accelerate the recovery of the falling FDI were discussed correspondently.

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Questions of the small size of non-industrial private forest (NIPF) holdings in Finland are considered and factors affecting their partitioning are analyzed. This work arises out of Finnish forest policy statements in which the small average size of holdings has been seen to have a negative influence on the economics of forestry. A survey of the literature indicates that the size of holdings is an important factor determining the costs of logging and silvicultural operations, while its influence on the timber supply is slight. The empirical data are based on a sample of 314 holdings collected by interviewing forest owners in the years 1980-86. In 1990-91 the same holdings were resurveyed by means of a postal inquiry and partly by interviewing forest owners. The principal objective in compiling the data is to assist in quantifying ownership factors that influence partitioning among different kinds of NIPF holdings. Thus the mechanism of partitioning were described and a maximum likelihood logistic regression model was constructed using seven independent holding and ownership variables. One out of four holdings had undergone partitioning in conjunction with a change in ownership, one fifth among family owned holdings and nearly a half among jointly owned holdings. The results of the logistic regression model indicate, for instance, that the odds on partitioning is about three times greater for jointly owned holdings than for family owned ones. Also, the probabilities of partitioning were estimated and the impact of independent dichotomous variables on the probability of partitioning ranged between 0.02 and 0.10. The low value of the Hosmer-Lemeshow test statistic indicates a good fit of the model and the rate of correct classification was estimated to be 88 per cent with a cutoff point of 0.5. The average size of holdings undergoing ownership changes decreased from 29.9 ha to 28.7 ha over the approximate interval 1983-90. In addition, the transition probability matrix showed that the trends towards smaller size categories mostly involved in the small size categories, less than 20 ha. The results of the study can be used in considering the effects of the small size of holdings for forestry and if the purpose is to influence partitioning through forest or rural policy.

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The aim of this study is to find out how urban segregation is connected to the differentiation in educational outcomes in public schools. The connection between urban structure and educational outcomes is studied on both the primary and secondary school level. The secondary purpose of this study is to find out whether the free school choice policy introduced in the mid-1990´s has an effect on the educational outcomes in secondary schools or on the observed relationship between the urban structure and educational outcomes. The study is quantitative in nature, and the most important method used is statistical regression analysis. The educational outcome data ranging the years from 1999 to 2002 has been provided by the Finnish National Board of Education, and the data containing variables describing the social and physical structure of Helsinki has been provided by Statistics Finland and City of Helsinki Urban Facts. The central observation is that there is a clear connection between urban segregation and differences in educational outcomes in public schools. With variables describing urban structure, it is possible to statistically explain up to 70 % of the variation in educational outcomes in the primary schools and 60 % of the variation in educational oucomes in the secondary schools. The most significant variables in relation to low educational outcomes in Helsinki are abundance of public housing, low educational status of the adult population and high numbers of immigrants in the school's catchment area. The regression model has been constructed using these variables. The lower coefficient of determination in the educational outcomes of secondary schools is mostly due to the effects of secondary school choice. Studying the public school market revealed that students selecting a secondary school outside their local catchment area cause an increase in the variation of the educational outcomes between secondary schools. When the number of students selecting a school outside their local catchment area is taken into account in the regressional model, it is possible to explain up to 80 % of the variation in educational outcomes in the secondary schools in Helsinki.